Today's connected car systems are a storehouse of data. These cars are not only improving consumer experiences but also offering revenue and cost benefits to mobility companies, including OEMs, car dealers, suppliers, tech players, and much beyond. The automotive industry is increasingly open to harnessing data from connected cars. To assist mobility companies seeking opportunities in this domain, surveys have come up with an evaluation of the potential market value of data-driven services. HeadSpin’s analysis explores promising use cases and identifies strategic approaches to enhance their prospects for success.
Monetization opportunity for OEMs and other mobility sectors
Consumers highly value connectivity, as evidenced by one of McKinsey's surveys, where 37 percent expressed a willingness to switch car brands for connectivity improvements. In some regions, this figure was even higher, such as 56 percent in China. Moreover, 39 percent of consumers showed interest in unlocking additional digital features post-purchase, rising to 47 percent among premium OEM customers. Failure to meet these connectivity expectations can lead to customer attrition.
Numerous OEMs have grappled with challenges related to connectivity and software development, resulting in unfavorable customer feedback and project delays. Only a select few have managed to excel in the realm of software-defined vehicles and effectively capitalize on vehicle data monetization. These successful companies concentrate on three pivotal activities:
- Extensive data access: Enabling continuous improvements by granting access to 1 to 2 terabytes of daily vehicle data.
- Monetization: Emphasizing monetization through subscriptions and paid OTA upgrades.
- Swift integration: Achieving rapid idea-to-vehicle integration in about six weeks, a strategy that has benefited EV-focused OEMs.
Connected car performance analysis is also presenting clear monetization opportunities today. Connected vehicles generate valuable data streams. OEMs can explore monetization opportunities by providing data-driven services to third parties, such as insurance companies, advertisers, and smart city initiatives. This diversification of revenue streams can bolster OEM profitability.
However, most companies are much less successful in optimally monetizing the situation, and the primary reasons include:
1. Failing to capture customer interest and distinguish their services
To engage customers effectively, OEMs must differentiate their services from the wealth of connectivity offerings available on smartphones. Complex onboarding processes, service execution issues, and communication challenges hinder consumer adoption. In the B2B realm, many customers remain unaware of car data's potential benefits, resulting in underutilization.
2. Neglecting organizational transformation
Companies need to restructure and develop dedicated cross-functional units to monetize data effectively across the vehicle's lifecycle. Siloed functions, talent gaps, and outdated business models hamper progress.
3. Overlooking ecosystem development for scalability
Automakers should collaborate with existing service providers for rapid scaling in areas like automated charging, remote monitoring, and targeted advertising. Isolated solutions hinder core competency focus and limited partnerships in the B2B space limit market reach. This landscape is evolving, though.
How have connected cars reformed the current automobile landscape?
- Enhanced safety: Advanced driver assistance systems (ADAS) use real-time data to provide features like lane-keeping assistance, adaptive cruise control, and collision avoidance, significantly improving driver safety.
- Convenience: Features such as remote engine start, climate control, and vehicle diagnostics can be accessed through mobile apps, offering drivers unparalleled convenience.
- Efficiency: Real-time traffic data helps optimize route planning, reducing travel time and fuel consumption.
- Entertainment: Infotainment systems provide passengers with internet access, streaming services, and more, making journeys more enjoyable.
However, to completely garner the connected car systems, it is critical to test and validate these systems for optimized performance and user experiences. As a means to achieve this, automobile companies are focusing on leveraging real-time connected car analytics end-to-end.
Importance of real-time connected car analytics in automobile testing
The automotive industry, in several scenarios, is shifting towards digitization, connectivity, and data-driven decision-making, making real-time analytics an indispensable tool for manufacturers, service providers, and consumers alike.
The primary factors making real-time analytics a key are:
● Improved testing precision
Real-time connected car analytics provide testers with a continuous stream of data from various vehicle sensors and systems. This influx of real-time data allows for more precise and dynamic testing scenarios. Testers can monitor critical parameters such as engine performance, braking, suspension, and emissions in real-time, enabling them to detect and address issues promptly.
● Simulated real-world testing
Modern vehicles are equipped with several sensors and communication modules that capture data during real-world driving conditions. Real-time analytics enable testers to replicate conditions like these in a controlled environment, such as a test track or simulation facility. This simulation of real-world scenarios helps assess a vehicle's behavior under different driving conditions, from urban traffic to highway speeds.
● Early issue detection
Real-time analytics provide instant feedback on a vehicle's performance, allowing testers to identify and address issues as they occur. This proactive approach to issue detection is invaluable in preventing potentially costly recalls and safety hazards. It ensures that vehicles meet regulatory standards and consumer expectations.
● Safety validation
Safety is a paramount concern in the automotive industry. Real-time connected car analytics enable safety validation tests to be conducted more comprehensively. Testers can monitor critical safety systems such as adaptive cruise control, collision avoidance, and lane-keeping assistance in real-time. This validation process helps ensure that these systems function correctly and reliably, reducing the risk of accidents.
● Efficient data analysis for performance
Real-time analytics streamline the process of data analysis during testing. Instead of manually collecting and processing data after each test, testers can rely on automated systems that provide immediate insights. This efficiency accelerates the testing cycle, allowing manufacturers to bring vehicles to market faster while enhancing connected car-performance analysis.
In the event of a vehicle recall, connected car performance analysis helps OEMs pinpoint affected vehicles with precision. This targeted approach ensures that only vehicles at risk are recalled, minimizing disruption for unaffected customers.
The common challenges faced by OEMs while leveraging real-time analytics in testing
Following are the major challenges faced while testing the connected car applications.
Consumer demands around mobile-at-par experiences: Very often, consumers expect infotainment systems to deliver experiences equivalent to mobile experiences in terms of responsiveness, loading time, and features like communication, music, and other entertainment features. This makes testing complex in terms of catering to multiple requirements of users.
Complex and time-consuming testing and optimization processes: Testing connected car applications involves complex scenarios, such as real-time data streaming and integration with various vehicle systems. This complexity often leads to lengthy testing and optimization processes, affecting time-to-market.
Stringent requirements for addressing potential safety concerns: As connected cars keep evolving in terms of comfort and safety across networked vehicle components and systems, the testing requirements become more and more complex. The introduction of new features and information in connected cars can lead to driver distractions. Ensuring that the user interface and interactions do not compromise safety is a critical challenge. Additionally, with cars becoming more connected with external sources, for instance, vehicle-to-vehicle, vehicle-to-infrastructure, and vehicle-to-cloud, the connected cars require more efficient and extensive testing to ensure the reliable and safe operation of these complex systems.
Resolving connectivity issues affecting user experience: Connectivity issues can disrupt the user experience. This includes challenges related to maintaining a stable connection to the internet, ensuring consistent data transfer, and handling network transitions seamlessly.
Testing in geo-distributed teams: The connected cars require multiple sub-components from different sources, such as the cameras, proximity sensors, user touch, display units, and much more. Different components need to be tested and monitored by different teams in different locations, which makes it difficult to seamlessly manage testing labs across multiple geographies. This often leads to resource limitations and inefficient testing, thereby compromising the results.
The aspects to be tested in connected cars
- In-vehicle infotainment testing: In-vehicle infotainment systems are a central component of connected cars, providing entertainment, navigation, and connectivity features to users. Testing should focus on verifying the functionality of multimedia interfaces, touchscreen responsiveness, audio quality, voice recognition, and compatibility with external devices such as smartphones and tablets. It also includes testing the integration of software applications, ensuring they work seamlessly within the infotainment ecosystem. The goal is to deliver a rich and intuitive infotainment experience to drivers and passengers.
- Connected user experiences: Connected cars rely on various sensors, connectivity protocols, and data exchange mechanisms to offer a range of user experiences. Testing in this area encompasses evaluating how well these systems perform in real-world scenarios. It involves testing the reliability of connectivity, including Bluetooth, Wi-Fi, and cellular networks, to ensure uninterrupted access to services and data. Additionally, user experiences related to remote vehicle control, over-the-air (OTA) updates, and vehicle-to-infrastructure (V2I) communication must be thoroughly tested to guarantee a smooth and secure interaction between the car and its ecosystem.
- Cybersecurity and data privacy: As connected cars become increasingly reliant on data exchange, ensuring the security and privacy of both vehicle and user data is paramount. Testing should focus on identifying vulnerabilities and weaknesses in the car's network architecture, data transmission, and storage mechanisms. This includes penetration testing to assess the car's resistance to cyberattacks. Additionally, data privacy testing evaluates whether user data, including personal information and driving habits, is appropriately protected and compliant with relevant regulations such as GDPR. A robust cybersecurity strategy is essential to safeguarding both the vehicle and the user against potential threats.
Improving automobile testing with HeadSpin
HeadSpin's data science capabilities for automobile testing eliminate the complexities of testing connected vehicle applications, leveraging advanced analytics to evaluate vehicle performance, reliability, and user experience.
HeadSpin's solution for automobile testing allows OEMs to enhance development quality and streamline QA processes. This boosts the stability of each release cycle while minimizing rework and post-release investigations. The solution helps:
- Deploy real mobile devices to facilitate testing automation and support developers in their work.
- Measure pertinent performance metrics, ensuring comprehensive evaluation.
- Pinpoint functional and performance issues across 15 critical user scenarios.
- Access source code for all scripts is provided to the automotive OEM team, fostering transparency and collaboration.
- Integrate into the automotive OEM's CI/CD workflow, enabling post-build automated tests to identify performance regressions.
- Integrate with Grafana and alerting systems to enhance monitoring and response capabilities.
The primary elements constructing the testing solution include HeadSpin's PBox, AV Box, and the System App/SDK.
- The PBox supports remote manual and automated testing of the devices debuggable over USB
- The AV Box serves as the sound/light isolated enclosure for apps that require audio video testing, like the voice assistants
- Consumer system app/SDK helps precisely monitor the performance and user experience of Android-based IVI systems
The HeadSpin solution can be seamlessly deployed on the premises of the customer, shared cloud, client-dedicated cloud, or reverse bridge technique (unique to HeadSpin).
- The on-prem deployment involves deploying the solution into an isolated network managed by the customer where no traffic leaves this network.
- The client-dedicated cloud deployment option, however, creates significant traction as it provides dedicated devices for customers in the HeadSpin cloud and helps isolate customer services, configuration, data, devices, and hosts to a private subnet.
- HeadSpin's reverse bridge technique, or 'Create your own Lab,' simplifies the testing journeys for companies immensely by eliminating their limitations of accessing multiple test labs for different purposes across various locations. CYOL enables distributed testing from anywhere in the world with reduced latency access to remote devices owned by the customer.
How does the HeadSpin automobile solution work?
HeadSpin's approach to analyzing performance of real-time connected vehicle apps revolves around capturing essential data from devices strategically positioned in the client's user environments, all seamlessly connected to local networks or Wi-Fi. The diverse deployment options of the HeadSpin appliance ensure secure integration, allowing it to seamlessly mesh with a variety of automated frameworks such as Appium, Selenium, or third-party testing tools. Through remote control UI/debug bridge access, it enables comprehensive device management.
HeadSpin's deep ML-driven Platform harnesses this data to:
In addition to these capabilities, HeadSpin's insightful visualizations and analytics dashboards are equipped with customizable KPI tracking. These features make it possible to gain a comprehensive understanding of system performance.
HeadSpin's automotive solutions are versatile, catering to three primary use cases: Infotainment System Testing, HeadSpin SDK for Android Automotive OS, and connected vehicle apps testing. This adaptability empowers automotive companies to analyze connected vehicle apps to optimize their performance and ensure unparalleled user experiences.
HeadSpin's robust approach to data capture, analysis, and performance optimization allows for effective monitoring of real-time connected vehicle apps and facilitates comprehensive performance analysis, enabling it to proactively address issues, enhance user experiences, and drive innovation in the rapidly evolving automotive landscape.
What does HeadSpin offer?
In today's automotive landscape, consumers expect in-vehicle infotainment experiences that rival the seamless interactions they enjoy on their smartphones.
To meet these expectations, HeadSpin offers innovative in-vehicle infotainment testing solutions that leverage data science and real-time feedback to drive performance improvements.
Key focus areas:
- User experience enhancement: HeadSpin's in-vehicle infotainment testing focuses on improving the overall user experience within the vehicle cabin, ensuring that drivers and passengers have access to cutting-edge entertainment and information systems.
- Driver distraction mitigation: In connected vehicles, IVI units are critical in ensuring seamless performance of not only the car but also the driver’s concentration. In case of a glitch in the IVIS in terms of navigation, or music players, and many more can easily jeopardize safety by distracting the driver. HeadSpin’s testing solutions help identify and address potential driver distractions, ensuring a safer driving environment.
- Quality of service: HeadSpin delivers the highest quality service by constantly monitoring and optimizing the performance of in-vehicle infotainment systems.
What does HeadSpin offer for enhancing automotive digital experience?
1. Connected vehicle application testing
HeadSpin’s deep ML models enable OEMs to analyze and monitor core KPIs that impact the performance and user experience of the CV apps. The ML driven Platform and the PBox help monitor the real time user experience of key features of the app like car lock and unlock, window up, bluetooth and much more allowing users to leverage the device as a key to controlling the vehicle (or Phone as a Key/PaaK).
This capability allows:
- Calculating latency for every use case
- Obtaining historical information, including improvements and degradations
- Calculating Bluetooth connection drop and performance matrix
- Obtaining insights into noisy environment effects and performance data
2. In-vehicle infotainment unit testing
HeadSpin allows OEMs to reverse bridge IVI units to test remotely and capture critical KPIs to improve user experiences. HeadSpin deploys advanced data science capabilities to close the feedback loop for infotainment and in-cabin digital experience measurement, thereby offering seamless driving experiences.
HeadSpin's system app seamlessly integrates with the vehicle's infotainment system, enabling real-time issue capture directly through the HeadSpin UI. This innovative approach empowers HeadSpin to pinpoint critical user journeys, identify UX issues at every step, and provide a range of solutions to address these issues, all with the ultimate goal of achieving optimal performance for the infotainment system.
3. SDK for Android automotive OS
HeadSpin provides SDKs (Software Development Kits) designed for deployment in vehicles equipped with Android Automotive OS. These SDKs facilitate various testing scenarios, including in-lab testing, in-drive testing, and end-to-end user experience monitoring.
HeadSpin continuously monitors the driver or user interaction with the Head Unit and Infotainment system. Testers gain access to real-time user data, enabling constant feedback and improvement efforts. This monitoring process captures key performance indicators (KPIs) such as blank screens, network errors, distracting screens, poor connectivity, loading animations, and instances of rage tapping.
The value HeadSpin adds to businesses
HeadSpin solutions empower auto companies to:
- Improve user experiences through proactive repairs and better service, resulting in higher Net Promoter Scores (NPS).
- Increase revenue by delivering superior infotainment experiences attracting and retaining customers who value these features.
- Monetize infotainment unit data, opening up new opportunities for the auto industry. For example, insurance companies can analyze various aspects of car usage to determine accurate premium rates.
- Discover how HeadSpin's In-Vehicle Infotainment Testing can transform your automotive offerings and enhance user satisfaction.
The automotive connectivity landscape is evolving at an unprecedented pace, offering substantial opportunities for data monetization across the entire ecosystem. Key beneficiaries include data suppliers like OEMs and vehicle fleets, as well as insurance companies, automotive aftermarket businesses, municipalities, infrastructure providers, and various data consumers. It's essential for all stakeholders to take swift action to harness these opportunities effectively.
HeadSpin's solutions are the right match for streamlining automobile testing with the unique advantages of executing tests across any location and testing in-car experiences as well as car app experiences for all users.
Leverage HeadSpin for every vehicle, every driver, and every engagement across the automobile space.
Q1. What is V2X testing?
Ans: V2X (Vehicle-to-Everything) testing involves evaluating the communication and connectivity between vehicles and their surroundings, including infrastructure and other vehicles, to ensure safety and efficiency.
Q2. How does telematics testing ensure data security?
Ans: Telematics testing assesses the security of data transmitted between vehicles and external servers, ensuring protection against cyber threats.
Q3. Why is open-loop and closed-loop testing important in autonomous vehicle development?
Ans: Open-loop testing simulates real-world scenarios in a controlled environment, while closed-loop testing evaluates vehicle responses to dynamic, unpredictable situations, both essential for validating autonomous systems.